Kubernetes–Setup a local cluster through Podman Desktop

Running a local Kubernetes cluster is easy thanks to Podman Desktop and Kind. In this post I show you how to setup a kind environment from Podman Desktop.

But first an introduction…

What is Podman Desktop?

Podman Desktop is an open source graphical tool enabling you to seamlessly work with containers and Kubernetes from your local environment. It offers similar functionality as Docker Desktop.

Installing Podman Desktop(on Windows) is easy:

Download the Windows installer.
Start the Podman Desktop installer, open the downloaded file.

Podman Desktop uses WSL2 to run a a Linux distribution in a virtual machine. It can be that a restart is required as the installer will try to enable/install WSL2 during the process.

More information: Windows | Podman Desktop (podman-desktop.io)

What is Kind?

Kind is an open source project that allows to run Kubernetes clusters in a container engine (could be Docker or Podman or others). This is usually quite helpful for development and testing purposes, as you can run a Kubernetes locally in a lightweight fashion.

The easiest way to install Kind on Windows is through the Chocolatey package manager:

choco install kind

Run Kubernetes in Podman Desktop

Now that all required components are installed, we can create our local Kubernetes cluster.

Open Podman Desktop and go to Settings

Click on Resources and choose Create new… to create a new Podman machine (you can skip this step and the next if you already have a Podman machine running.

Specify a name, # of CPU’s, an amount of memory and click on Create.

Now go to the Kind section in the Resources and click on Create new …

Specify a name, leave the other settings intact and click on Create.

The first time I did this, it failed with the following error message in the logs:

This is because Podman creates the machine by default in rootless mode. However when running the Podman machine on WSL in combination with Kind a rootful machine is needed. Therefore we need to take the following actions:

Stop the podman machine

podman machine stop

Set the machine in rootful mode:

podman machine set --rootful

Restart the machine:

podman machine start

Let’s now try again to create a local cluster:

Go to the Kind section in Resources and click on Create new …
Specify a name, leave the other settings intact and click on Create.

Once the cluster is created, we can change the Kubernetes context to use our newly created cluster.

Click on the Kubernetes icon in the status bar of Podman Desktop at the bottom and select the correct cluster from the drop down.

Finally we are ready to start adding our first pods:

Go to the Pods screen, click the Play Kubernetes YAML button and select a yaml file that contains the Pod metadata.

You are good to go!

Podman– Command execution failed with exit code 125

After updating WSL on one of the developer machines, Podman failed to work. When we took a look through Podman Desktop, we noticed that Podman had stopped running and returned the following error message: Error: Command execution failed with exit code 125 Here are the steps we tried to fix the issue: We started by running podman info to get some extra details on what could be wrong: >podman info OS: windows/amd64 provider: wsl version: 5.3.1 Cannot connect to Podman. Please verify your connection to the Linux system using `podman system connection list`, or try `podman machine init` and `podman machine start` to manage a new Linux VM Error: unable to connect to Podman socket: failed to connect: dial tcp 127.0.0.1:2655: connectex: No connection could be made because the target machine actively refused it. That makes sense as the podman VM was not running. Let’s check the VM: >podman machine list NAME ...

Cache stampede: when our cache turned against us

While investigating some performance issues, we ran into an ASP.NET Core API that cached a fairly expensive aggregation query for 60 seconds. Under normal load, that was fine: one request rebuilds the cache, everyone else reads from it. Under peak load, dozens of requests would arrive in that same expiry window, all see a cache miss, and all fire the same expensive query in parallel. The database didn't like that. That was the moment when our caching layer stopped helping and started hurting. A burst of requests comes in at the same time, all miss the cache, and all go hammer the database or the downstream API at once. That's a cache stampede . The cache was supposed to protect our backend, and for a few hundred milliseconds it did the opposite. Why this happens IMemoryCache.GetOrCreate (and its async sibling) looks like it protects you, but it doesn't add any locking on its own. Look at the naive version: public async Task<Report> GetReportAsync(string key) ...

VS Code Planning mode

After the introduction of Plan mode in Visual Studio , it now also found its way into VS Code. Planning mode, or as I like to call it 'Hannibal mode', extends GitHub Copilot's Agent Mode capabilities to handle larger, multi-step coding tasks with a structured approach. Instead of jumping straight into code generation, Planning mode creates a detailed execution plan. If you want more details, have a look at my previous post . Putting plan mode into action VS Code takes a different approach compared to Visual Studio when using plan mode. Instead of a configuration setting that you can activate but have limited control over, planning is available as a separate chat mode/agent: I like this approach better than how Visual Studio does it as you have explicit control when plan mode is activated. Instead of immediately diving into execution, the plan agent creates a plan and asks some follow up questions: You can further edit the plan by clicking on ‘Open in Editor’: ...

The art of simplicity

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